{"id":"https://openalex.org/W4388192902","doi":"https://doi.org/10.1145/3581783.3612355","title":"Modality-agnostic Augmented Multi-Collaboration Representation for Semi-supervised Heterogenous Face Recognition","display_name":"Modality-agnostic Augmented Multi-Collaboration Representation for Semi-supervised Heterogenous Face Recognition","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4388192902","doi":"https://doi.org/10.1145/3581783.3612355"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3612355","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3612355","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058058294","display_name":"Decheng Liu","orcid":"https://orcid.org/0000-0002-6550-212X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Decheng Liu","raw_affiliation_strings":["Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049498576","display_name":"Weizhao Yang","orcid":"https://orcid.org/0009-0002-6891-3511"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weizhao Yang","raw_affiliation_strings":["Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012655281","display_name":"Chunlei Peng","orcid":"https://orcid.org/0000-0003-3448-2514"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunlei Peng","raw_affiliation_strings":["Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100690630","display_name":"Nannan Wang","orcid":"https://orcid.org/0000-0003-1435-489X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nannan Wang","raw_affiliation_strings":["Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087726516","display_name":"Ruimin Hu","orcid":"https://orcid.org/0000-0002-0290-5757"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruimin Hu","raw_affiliation_strings":["Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101785348","display_name":"Xinbo Gao","orcid":"https://orcid.org/0000-0003-1443-0776"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinbo Gao","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5058058294"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":1.324,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.83200387,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4647","last_page":"4656"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7770476341247559},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.7217309474945068},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6868881583213806},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6237853765487671},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5734474658966064},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.547467827796936},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.5458028316497803},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5327558517456055},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5156922936439514},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4840647280216217},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.4758167862892151},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4270244836807251},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3608301281929016},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.10748887062072754}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7770476341247559},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.7217309474945068},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6868881583213806},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6237853765487671},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5734474658966064},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.547467827796936},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.5458028316497803},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5327558517456055},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5156922936439514},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4840647280216217},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.4758167862892151},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4270244836807251},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3608301281929016},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10748887062072754},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3581783.3612355","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3612355","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1607277929","https://openalex.org/W2030899956","https://openalex.org/W2038809248","https://openalex.org/W2085810284","https://openalex.org/W2157032359","https://openalex.org/W2186500555","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2325658686","https://openalex.org/W2523746035","https://openalex.org/W2620998106","https://openalex.org/W2798807671","https://openalex.org/W2801271986","https://openalex.org/W2962858109","https://openalex.org/W2963073614","https://openalex.org/W2963460857","https://openalex.org/W2963600167","https://openalex.org/W2963639219","https://openalex.org/W2963809521","https://openalex.org/W2963857521","https://openalex.org/W2963968629","https://openalex.org/W2987861506","https://openalex.org/W2997006708","https://openalex.org/W3000566195","https://openalex.org/W3006602891","https://openalex.org/W3018746726","https://openalex.org/W3034552680","https://openalex.org/W3034956129","https://openalex.org/W3035682985","https://openalex.org/W3047180765","https://openalex.org/W3081668972","https://openalex.org/W3096831136","https://openalex.org/W3118405827","https://openalex.org/W3125695697","https://openalex.org/W3127511859","https://openalex.org/W3129371451","https://openalex.org/W3132834324","https://openalex.org/W3184953896","https://openalex.org/W3194919257","https://openalex.org/W3195126276","https://openalex.org/W3195286673","https://openalex.org/W4225243029","https://openalex.org/W4285254934","https://openalex.org/W4313071719","https://openalex.org/W4313128368"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378510483","https://openalex.org/W3040691452"],"abstract_inverted_index":{"Heterogeneous":[0,79],"face":[1,8,127],"recognition":[2],"(HFR)":[3],"aims":[4],"to":[5,15,53,62,93,97,111],"match":[6],"input":[7],"identity":[9],"across":[10],"different":[11],"image":[12],"modalities.":[13],"Due":[14],"the":[16,22,55,64,102,113,138],"existing":[17],"large":[18],"modality":[19,46,56],"gap":[20],"and":[21,36,39,133],"limited":[23],"number":[24],"of":[25],"training":[26],"data,":[27],"HFR":[28],"is":[29,91,109,152],"still":[30],"a":[31,72,84],"challenging":[32],"problem":[33],"in":[34,83],"biometrics":[35],"draws":[37],"more":[38,40],"attention.":[41],"Existing":[42],"researchers":[43],"always":[44],"extract":[45],"invariant":[47],"features":[48],"or":[49],"generate":[50,94],"homogeneous":[51],"images":[52],"decrease":[54],"gap,":[57],"lacking":[58],"abundant":[59],"labeled":[60],"data":[61],"avoid":[63],"overfitting":[65],"problem.":[66],"In":[67],"this":[68],"paper,":[69],"we":[70],"proposed":[71,92,139],"novel":[73],"Modality-Agnostic":[74],"Augmented":[75],"Multi-Collaboration":[76],"representation":[77],"for":[78,119],"Face":[80,135],"Recognition":[81],"(MAMCO-HFR)":[82],"semi-supervised":[85],"manner.":[86],"The":[87,105,149],"modality-agnostic":[88,103],"augmentation":[89],"strategy":[90],"adversarial":[95],"perturbations":[96],"map":[98],"unlabeled":[99],"faces":[100],"into":[101],"domain.":[104],"multi-collaboration":[106],"feature":[107],"constraint":[108],"designed":[110],"mine":[112],"inherent":[114],"relationships":[115],"between":[116],"diverse":[117],"layers":[118],"discriminative":[120],"representation.":[121],"Experiments":[122],"on":[123],"several":[124],"large-scale":[125],"heterogeneous":[126],"datasets":[128],"(CASIA":[129],"NIR-VIS":[130],"2.0,":[131],"LAMP-HQ":[132],"Tufts":[134],"dataset)":[136],"prove":[137],"algorithm":[140],"can":[141],"achieve":[142],"superior":[143],"performance":[144],"compared":[145],"with":[146],"state-of-the-art":[147],"methods.":[148],"source":[150],"code":[151],"available":[153],"at":[154],"https://github.com/xiyin11/Semi-HFR.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}